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Even if in reality the relationship between the inputs and the outcome to be predicted might not be causal, we can see the inputs of a model as the cause of the prediction.a.Falseb.True

Question

Even if in reality the relationship between the inputs and the outcome to be predicted might not be causal, we can see the inputs of a model as the cause of the prediction.a.Falseb.True

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Solution

b. True. Even if the relationship between the inputs and the outcome is not causal in reality, in the context of a model, we can view the inputs as the cause of the prediction. This is because the model uses the inputs to generate or 'cause' the prediction. However, it's important to note that this doesn't imply a real-world causal relationship between the inputs and the outcome.

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Causation vs. Causality: Clarify the difference with planning-related examples

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• Causation vs. Causality: Clarify the difference with planning-related examples

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